Fast Artificial Neural Network Library implements multilayer
artificial neural networks in C with support for both fully connected
and sparsely connected networks. Cross-platform execution in both
fixed and floating point are supported. It includes a framework for
easy handling of training data sets. It is easy to use, versatile,
well documented, and fast. Bindings to other programming languages
and a GUI are also available.

Log message:
Add SHA512 digests for distfiles for devel category
Issues found with existing distfiles:
distfiles/eclipse-sourceBuild-srcIncluded-3.0.1.zip
distfiles/fortran-utils-1.1.tar.gz
distfiles/ivykis-0.39.tar.gz
distfiles/enum-1.11.tar.gz
distfiles/pvs-3.2-libraries.tgz
distfiles/pvs-3.2-linux.tgz
distfiles/pvs-3.2-solaris.tgz
distfiles/pvs-3.2-system.tgz
No changes made to these distinfo files.
Otherwise, existing SHA1 digests verified and found to be the same on
the machine holding the existing distfiles (morden). All existing
SHA1 digests retained for now as an audit trail.

Log message:
Add newline to separate decls, but really to provoke a commit.
Commit message that should have been in previous commit follows:
Version 2.2.0 is backwards compatible and adds the following new
features:
Added Sarprop training
Added fann_create_train for creating an empty training data struct
Added fann_copy for copying an ANN
Added cascade_min_out_epochs and cascade_min_cand_epochs to
improve cascade training
Added extra checks when training, to ensure that data and network
input and output sizes matches
Added Visual Studio 2010 solution
Added support for 64bit architecture
Cleanup in sources
Moved source from CVS to GIT